This paper provides a direct comparison of two stochastic optimisation techniques (Markov Chain Monte Carlo and Sequential Monte Carlo) when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The two methods are then also compared to another existing technique of Mixed-Integer Linear Programming which is also popular in distributed control.
This paper presents the parallelisation of a Se quential Monte Carlo algorithm, and the associated changes required when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The target problem is non-linear constrained, non-convex and multi-agent. The new method is ' shown to have a 98.5% computational time saving over that of a previous sequential implementation, with no degradation in path quality. The computation saving is enough to allow real-time implementation.
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